What Can We Learn From Energy Consumption on Excess Stock Return Prediction?
Fei Lü et al.
What the paper says
Stock market return prediction has long been a focal point within the realm of financial research. This study introduces a novel series of energy consumption indicators, predicated on economic constraints, to forecast stock market excess returns. Empirical results indicate that these newly constructed indicators are instrumental in predicting excess returns. Moreover, the combination models consistently outperform other competing models, especially under the constraint method based on the Sharpe ratio. We also highlight that energy consumption indicators maintain robust performance during periods of financial turbulence, such as the financial crisis and the COVID‐19 pandemic, with a notable emphasis on non‐renewable energy consumption from the commercial sector. Our findings offer valuable insights into forecasting stock market returns from an energy consumption perspective.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.